The Environmental Kuznets Curve (EKC) hypothesis -an inverted U-shape relation between various indicators of environmental degradation and income per capitahas become one of the 'stylised facts' of environmental and resource economics. This is despite considerable criticism on both theoretical and empirical grounds. Cointegration analysis can be used to test the validity of such stylised facts when the data involved contain stochastic trends. In the present paper, we use cointegration analysis to test the EKC hypothesis using a panel dataset of sulfur emissions and GDP data for 74 countries over a span of 31 years. We find that the data is stochastically trending in the time-series dimension. Given this, and interpreting the EKC as a long run equilibrium relationship, support for the hypothesis requires that an appropriate model cointegrates and that sulfur emissions are a concave function of income. Individual and panel cointegration tests cast doubt on the general applicability of the hypothesised relationship. Even when we find cointegration, many of the relationships for individual countries are not concave. The results show that the EKC is a problematic concept, at least in the case of sulfur emissions.

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The paper examines whether or not evidence is consistent with convergence of the Okun's Law coefficient (OLC) among several alternative groupings of European economies. A two-step empirical strategy is employed. The first step obtains rolling regression estimates of the OLC for individual European countries. The second step examines how the cross-country variance of the OLC evolves over the decade until 2002 in the selected country groupings. Evidence is found consistent with convergence of the OLC among northern European countries, and among countries with centralized wage bargaining, but an absence of convergence in other country groups.

An overview of the cointegration approach to econometric specification and estimation is provided. A non‐technical approach is adopted, and is intended to serve as an entry into this important new literature for the reader with no background knowledge of the subject but with some limited knowledge of econometrics. Particular emphases are given to the rationale for using cointegration techniques in the estimation of economic relationships, to providing intuitive explanations of the concepts and techniques, and to demonstrating their applications in practice. Reference is made throughout to other articles which explain particular methods or recent developments more formally and fully than is possible here. Finally, a simple application of cointegration techniques to the estimation of the consumption function is provided.

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